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Incremental Cardinality Constraints for MaxSAT
"... Maximum Satisfiability (MaxSAT) is an optimization variant of the Boolean Satisfiability (SAT) problem. In general, MaxSAT algorithms perform a succession of SAT solver calls to reach an optimum solution making extensive use of cardinality constraints. Many of these algorithms are nonincremental i ..."
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Cited by 2 (0 self)
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Maximum Satisfiability (MaxSAT) is an optimization variant of the Boolean Satisfiability (SAT) problem. In general, MaxSAT algorithms perform a succession of SAT solver calls to reach an optimum solution making extensive use of cardinality constraints. Many of these algorithms are non
Incremental Cardinality Constraints for MaxSAT‡
"... Abstract. Maximum Satisfiability (MaxSAT) is an optimization variant of the Boolean Satisfiability (SAT) problem. In general, MaxSAT algorithms perform a succession of SAT solver calls to reach an optimum solution making extensive use of cardinality constraints. Many of these algorithms are nonincr ..."
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Abstract. Maximum Satisfiability (MaxSAT) is an optimization variant of the Boolean Satisfiability (SAT) problem. In general, MaxSAT algorithms perform a succession of SAT solver calls to reach an optimum solution making extensive use of cardinality constraints. Many of these algorithms are non
Reformulation based MaxSAT robustness
"... The use of SAT and MaxSAT encodings for solving constraint satisfaction problems (CSP) has been gaining wide acceptance in the last years. On the other hand, the presence of uncertainty in the real world makes robustness to be a desired property of solutions to CSPs. Roughly speaking, a solution is ..."
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The use of SAT and MaxSAT encodings for solving constraint satisfaction problems (CSP) has been gaining wide acceptance in the last years. On the other hand, the presence of uncertainty in the real world makes robustness to be a desired property of solutions to CSPs. Roughly speaking, a solution
Solving MaxSAT and #SAT on structured CNF formulas
 In C. Sinz & U. Egly (Eds.), SAT
, 2014
"... In this paper we propose a structural parameter of CNF formulas and use it to identify instances of weighted MaxSAT and #SAT that can be solved in polynomial time. Given a CNF formula we say that a set of clauses is precisely satisfiable if there is some complete assignment satisfying these clauses ..."
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Cited by 2 (1 self)
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In this paper we propose a structural parameter of CNF formulas and use it to identify instances of weighted MaxSAT and #SAT that can be solved in polynomial time. Given a CNF formula we say that a set of clauses is precisely satisfiable if there is some complete assignment satisfying these clauses
An Approximation Algorithm for MAX2SAT with Cardinality Constraint
 PROCEEDINGS OF THE 11TH ANNUAL EUROPEAN SYMPOSIUM ON ALGORITHMS, 301– 312
, 2003
"... We present a randomized polynomialtime approximation algorithm for the MAX2SAT problem in the presence of an extra cardinality constraint which has an asymptotic worstcase ratio of 0.75. This improves upon the previously best approximation ratio 0.6603 which was achieved by Bläser and Manthey ..."
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Cited by 3 (0 self)
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We present a randomized polynomialtime approximation algorithm for the MAX2SAT problem in the presence of an extra cardinality constraint which has an asymptotic worstcase ratio of 0.75. This improves upon the previously best approximation ratio 0.6603 which was achieved by Bläser and Manthey
Adding cardinality constraints to integer . . .
, 2007
"... MaxSATCC is the following optimization problem: Given a formula in CNF and a bound k, find an assignment with at most k variables being set to true that maximizes the number of satisfied clauses among all such assignments. If each clause is restricted to have at most ℓ literals, we obtain the prob ..."
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CC. We answer this question in the affirmative by presenting a randomized approximation algorithm whose approximation ratio is 1−(1 − 1 ℓ)ℓ −ε. To do this, we develop a general technique for adding a cardinality constraint to certain integer programs. Our algorithm can be derandomized using pairwise
An Efficient Bounds Consistency Algorithm for the Global Cardinality Constraint
 PROCEEDINGS CP
, 2003
"... Previous studies have demonstrated that designing special purpose constraint propagators can significantly improve the efficiency of a constraint programming approach. In this paper we present an efficient algorithm for bounds consistency propagation of the generalized cardinality constraint (gcc). ..."
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Cited by 24 (4 self)
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Previous studies have demonstrated that designing special purpose constraint propagators can significantly improve the efficiency of a constraint programming approach. In this paper we present an efficient algorithm for bounds consistency propagation of the generalized cardinality constraint (gcc
An Approximate MaxFlow MinCut Theorem for Uniform Multicommodity Flow Problems with Applications to Approximation Algorithms
, 1989
"... In this paper, we consider a multicommodity flow problem where for each pair of vertices, (u,v), we are required to sendf halfunits of commodity (uv) from u to v and f halfunits of commodity (vu) from v to u without violating capacity constraints. Our main result is an algorithm for performing th9 ..."
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Cited by 246 (12 self)
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can prove that any nnode bounded degree graph, G, with minimum edge expansion h can be configured offline to simulate any nnode bounded degree graph H in 0(log n/a)steps using constant size queues. By letting H be a universal network, we can then use G to simulate a PRAM online with elay 0(log2 n1
Online bin packing with cardinality constraints
 SIAM JOURNAL ON DISCRETE MATHEMATICS
"... We consider a one dimensional storage system where each container can store a bounded amount of capacity as well as a bounded number of items k ≥ 2. This defines the (standard) bin packing problem with cardinality constraints which is an important version of bin packing, introduced by Krause, Shen a ..."
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Cited by 8 (7 self)
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for variable sized bin packing, where each allowed bin size may have a distinct cardinality constraint, and for the resource augmentation model. All algorithms achieve the exact best possible competitive ratio possible for the given problem, and use constant numbers of open bins. Finally, we introduce
Approximation Algorithms for Knapsack Problems with Cardinality Constraints
 EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
, 1998
"... We address a variant of the classical knapsack problem in which an upper bound is imposed on the number of items that can be selected. This problem arises in the solution of reallife cutting stock problems by column generation, and may be used to separate cover inequalities with small support withi ..."
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Cited by 51 (3 self)
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We address a variant of the classical knapsack problem in which an upper bound is imposed on the number of items that can be selected. This problem arises in the solution of reallife cutting stock problems by column generation, and may be used to separate cover inequalities with small support
Results 1  10
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585